Empirical Legal Studies

Studying the "Tip of the Iceberg"

For empirical work focusing on the USSC, the Spaeth dataset continues to dominate. And access to the Spaeth dataset continues to dramatically improve. The most recent development involves the release of the Legacy Database, which includes "ready-to-use" data covering 1791-2014 (here; click here for a general description of the various data sets). An invaluable resource.

The Replication Crisis Continues to Spread

Now, evidently, biomedical research is beginning to confront replication problems of their own (click here and here for discussions). One factor that likely distinguishes biomedical research involves the magnitude of financial incentives and their influence.

Judge Data

Researchers using judge-level data will benefit from a new on-line judicial database created by the Free Law Project. Funded in part by NSF and foundation grants, and in conjunction with Elliot Ash (Princeton) and Bentley MacLeod (Columbia), the database currently includes biographical information on almost 8,500 federal and state judges. For more information, see the database's announcement (here) and the judge search engine (here).

Bayesian Umps

I previously linked to discussion of a paper assessing the degree to which Bayes Theorem informs judicial decisions. To the extent that judges aspire to play an "umpire" role (and in a slight bow to opening day), I note Andrew Gelman's (Columbia--Statistics) recent post (here) discussing the argument (developed in this paper) that Bayes Theorem informs baseball umpires' decisions on whether to call a "ball" or "strike."

CELS 2016 -- Call For Papers

The Eleventh Annual Conference on Empirical Legal Studies (CELS), hosted by Duke Law School, is scheduled for November 18-19, 2016, in Durham, NC. CELS brings together scholars from an array of fields, including law, economics, political science, psychology, and policy analysis. Papers are selected through a peer-review process and each is assigned an individual discussant. CELS invites empirical papers that span all areas of empirical legal studies. Authors are encouraged to submit works-in-progress; however, submissions should be completed paper drafts that include main results. Submitted papers must also be unpublished (and are expected to be unpublished at the time of the conference). Paper submission deadline is July 10, 2016.

Click here for additional conference information.

Judging Bayes' Theorem

The empirical literature seeking to understand judicial outcomes continues to develop and mature. Judge Posner's book, How Judges Think (2010), places Bayes' Theorem front-and-center. In a qualitative study of judges (N=30), Jack Knight (Duke), Mitu Gulati (Duke), and David Levy (Duke, and a former federal judge) set out to assess what Posner's book assumes. In How Bayesian Are Judges?, the authors conclude: "not at all." The abstract follows.

"Richard Posner famously modeled judges as Bayesians in his book, "How Judges Think?". A key element of being Bayesian is that one constantly updates with new information. This model of the judge who is constantly learning and updating, particularly about local conditions, also is one of the reasons why the factual determinations of trial judges are given deference on appeal. But do judges in fact act like Bayesian updaters? Judicial evaluations of search warrant requests for probable cause provides an ideal setting to examine this question because the judges in this context have access to information on how well they did on their probabilistic calculations (the officers who conduct the search have to file, in every case, a "return" detailing what was found in their search). Based on detailed interviews with thirty judges our answer to the "How Bayesian are Judges?" question is: Not at all. The puzzle we are left with, given that acting in a Bayesian fashion is normal behavior for the rest of us, is why we get these puzzling results for judges in the search warrant context?"